Detection of the papilla region and vessel detection on images of the retina are problems that can be solved with pattern recognition techniques. Topographic images, as provided e.g. by the HRT device, as well as fundus images can be used as source for the detection. It is of diagnostic importance to separate vessels inside the papilla area from those outside this area. Therefore, detection of the papilla is important also for vessel segmentation. In this contribution we present state of the art methods for automatic disk segmentation and compare their results. Vessels detected with matched filters (wavelets, derivatives of the Gaussian, etc.) are shown as well as vessel segmentation using image morphology. We present our own method for vessel segmentation based on a special matched filter followed by image morphology. In this contribution we argue for a new matched filter that is suited for large vessels in HRT images.
In this contribution we study the number of possible configurations up to discrete rotations of hyperedges built by using image neighborhood hypergraphs. Some results for texture classification are also presented.
In this contribution we present an interface for image processing algorithms that has been made recently available on the Internet (http://nibbler.uni-koblenz.de). First, we show its usefulness compared to some other existing products. After a description of its architecture, its main features are then presented: the particularity of the user management, its image database, its interface, and its original quarantine system. We finally present the result of an evaluation performed by students in image processing.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.